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A calibration simulation-based workflow using Qiskit
https://ipsj.ixsq.nii.ac.jp/records/240368
https://ipsj.ixsq.nii.ac.jp/records/240368f8b525b2-5d70-4b41-801f-b19dcbec3840
| 名前 / ファイル | ライセンス | アクション |
|---|---|---|
IPSJ-QS24013003.pdf (3.9 MB)
2026年10月21日からダウンロード可能です。
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Copyright (c) 2024 by the Information Processing Society of Japan
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| 非会員：¥660, IPSJ:学会員：¥330, QS:会員：¥0, DLIB:会員：¥0 | ||
| Item type | SIG Technical Reports(1) | |||||||||
|---|---|---|---|---|---|---|---|---|---|---|
| 公開日 | 2024-10-21 | |||||||||
| タイトル | ||||||||||
| タイトル | A calibration simulation-based workflow using Qiskit | |||||||||
| タイトル | ||||||||||
| 言語 | en | |||||||||
| タイトル | A calibration simulation-based workflow using Qiskit | |||||||||
| 言語 | ||||||||||
| 言語 | eng | |||||||||
| 資源タイプ | ||||||||||
| 資源タイプ識別子 | http://purl.org/coar/resource_type/c_18gh | |||||||||
| 資源タイプ | technical report | |||||||||
| 著者所属 | ||||||||||
| IBM Quantum／IBM Research - Tokyo | ||||||||||
| 著者所属 | ||||||||||
| IBM Quantum／IBM Research - Tokyo | ||||||||||
| 著者所属(英) | ||||||||||
| en | ||||||||||
| IBM Quantum / IBM Research - Tokyo | ||||||||||
| 著者所属(英) | ||||||||||
| en | ||||||||||
| IBM Quantum / IBM Research - Tokyo | ||||||||||
| 著者名 |
Kento, Ueda
× Kento, Ueda
× Naoki, Kanazawa
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| 著者名(英) |
Kento, Ueda
× Kento, Ueda
× Naoki, Kanazawa
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| 論文抄録 | ||||||||||
| 内容記述タイプ | Other | |||||||||
| 内容記述 | Quantum computing calibration is an essential process to maintain the accuracy of quantum gate operations. However, manual adjustments can be time-consuming and labor-intensive. This study proposes a calibration simulation workflow using Qiskit-Experiments and Qiskit-Dynamics, which enables error diagnosis through machine learning (ML) models. The work-flow generates datasets that include scenarios of both calibration successes and failures under various physical conditions. As a result, the trained models demonstrated high accuracy in identifying the causes of calibration errors. Additionally, we found that these models exhibited generalizability to different physical conditions, such as qubits with varying Hamiltonian parameters. This study contributes to the automation of quantum computer calibration and the efficiency of error diagnosis. The proposed workflow is expected to serve as a foundation for maintaining large-scale quantum computers in the future. | |||||||||
| 論文抄録(英) | ||||||||||
| 内容記述タイプ | Other | |||||||||
| 内容記述 | Quantum computing calibration is an essential process to maintain the accuracy of quantum gate operations. However, manual adjustments can be time-consuming and labor-intensive. This study proposes a calibration simulation workflow using Qiskit-Experiments and Qiskit-Dynamics, which enables error diagnosis through machine learning (ML) models. The work-flow generates datasets that include scenarios of both calibration successes and failures under various physical conditions. As a result, the trained models demonstrated high accuracy in identifying the causes of calibration errors. Additionally, we found that these models exhibited generalizability to different physical conditions, such as qubits with varying Hamiltonian parameters. This study contributes to the automation of quantum computer calibration and the efficiency of error diagnosis. The proposed workflow is expected to serve as a foundation for maintaining large-scale quantum computers in the future. | |||||||||
| 書誌レコードID | ||||||||||
| 収録物識別子タイプ | NCID | |||||||||
| 収録物識別子 | AA12894105 | |||||||||
| 書誌情報 |
研究報告量子ソフトウェア（QS） 巻 2024-QS-13, 号 3, p. 1-6, 発行日 2024-10-21 |
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| ISSN | ||||||||||
| 収録物識別子タイプ | ISSN | |||||||||
| 収録物識別子 | 2435-6492 | |||||||||
| Notice | ||||||||||
| SIG Technical Reports are nonrefereed and hence may later appear in any journals, conferences, symposia, etc. | ||||||||||
| 出版者 | ||||||||||
| 言語 | ja | |||||||||
| 出版者 | 情報処理学会 | |||||||||
